from IEEE The computer society 、 International Network Intelligence Association 、 Sponsored by the American computer society , At the university of Oxford, 、 University of Queensland 、 deakin university 、 Chinese Academy of Medical Sciences 、 Southeast University 、 Nanjing University of Finance and Economics 、PIESAT、 Taobao technology department 、IOS Press Co sponsored second 20 the WI-IAT international conference (WI-IAT 2021) On 2021 year 12 month 14 to 17 Held in Melbourne, Australia on the th .
WI-IAT It is an annual international conference in the field of artificial intelligence , It aims to provide a broad communication platform , For academia 、 Professionals and industry people share each other's ideas and findings . WI-IAT The goal is in collective intelligence 、 Data Science 、 knowledge management 、 Network science 、 To achieve a multidisciplinary balance between autonomous agent, human centered computing and the research progress of theories and methods related to multi-agent systems . meanwhile , Committed to solving the corresponding practical application problems , It not only deepens the calculation of the future network 、 Logic 、 cognition 、 Understanding of physical and social foundations , It also makes the development and application of intelligent technology possible .
This year is WI-IAT 20 Anniversary of the .WI-IAT'21 Provides a major forum , And in all theoretical and technical fields Web Intelligence and intelligent agent technology provide high-quality services 、 Original research papers and real-world applications . The theme of this conference is 'AI in the Connected World', namely AI Connect the world , Focus on AI The application and combination of technology to practical problems , Professional researchers at home and abroad have contributed a variety of contributions AI Technology to solve practical problems . The conference invited 2 Bitmap Spirit Award winner (Leslie Vialiant Professor and Joseph Sifakis professor )、 NAE member (Tom M. Mitchell professor ) And academicians of the Royal Dutch Academy of Sciences (Frank van Harmelen professor ) Share theme reports , And the promulgation of various awards . At this meeting , Taobao technology merchant empowerment algorithm team and Zhejiang University proposed TTNet The algorithm won “ Best industrial paper award ” prize .
Internet and digital technology have opened up new sales paths for small and medium-sized enterprises , Deeply promoted the marketing mode 、 Changes in consumer operation mode and commodity production mode . However, small and medium-sized businesses are often limited by their own sales scale 、 Lack of R & D capability and market publicity , It makes it difficult for their high-quality goods to be fully explored and grow by users in a large number of goods , Therefore, how to help small and medium-sized businesses reduce costs and improve efficiency in the process of commodity growth through digitization has always been the core problem of e-commerce market mechanism optimization , It is also the basis for e-commerce platforms to help society achieve common prosperity . The enabling algorithm team of Taobao technology merchants and Zhejiang University have innovatively brought Meta-transfer Learning The migration strategy is applied to Tabular Learning On , solve Tabular Data The problem of rapid adaptation in small sample migration , It contributes a new research idea to this field , Won the general assembly “ Best industrial paper ” prize .
After a lot of research work , The team further applied this algorithm model to tap new products of high-quality and potential businesses , Build from a small amount of sparse data Tabular Data characteristics , Then apply its proposed TTNet The algorithm model accurately and efficiently predicts the new product potential of merchants , New product potential can be used to guide the large-scale support and incubation of these potential new products . Proved by experiment , The team's algorithm model can tap the potential of 100 million new products , And the effective support of tens of millions of new businesses . In this way , This technology can help the high-quality new products of small and medium-sized businesses grow rapidly on the platform , Create new profit sources for businesses , It also brings a steady stream of high-quality new products to the platform , Expand the supply side resources of the platform , Provide consumers with more diversified choices .
Tabular Data is a common data format in daily life ( Such as spreadsheets and csv file ), It mainly includes tabular data such as categories and statistical data . Most of the existing methods, such as deep neural network, often can not mine this kind of data well Tabular features , Because compared with the tree structure method, it can not well realize feature selection . secondly , The existing methods are difficult to reuse because of the complex network structure , Furthermore, it can not achieve good performance results in the migration task . Therefore, in view of these two problems , The team put forward TTNet Algorithm , Its innovation is mainly reflected in :
- Firstly, by designing a box table network structure , It can imitate the tree structure to realize feature selection , It can also make the neural network realize network reuse in the migration task , In order to better mine the characteristics of tabular data .
- Besides , The team adopted Meta-transfer To realize the rapid adaptation of migrating from source data to target data .
(3) Whether in public data sets or in practical business data applications , Compared with the existing algorithms , The team put forward TTNet All methods can achieve better performance results .
The algorithm model can be widely used in general tablular Business scenario of data , Including but not limited to new product mining in the field of e-commerce , Risk account identification in the financial field , Patient health estimates in the medical field , We are committed to solving the problem of small data and sparse samples in business scenarios , Greatly improve the accuracy and efficiency of prediction . Taobao technology merchant empowerment algorithm team and Zhejiang University applied the algorithm model in the field of e-commerce , It has greatly improved the operation ability and digital ability of small and medium-sized businesses , Help businesses expand business benefits , Contribute to the common prosperity of society . Tang Xing, vice president of new retail technology business group of Taobao business group of Alibaba group, said ,“ This is a typical paradigm for technology to really play a role in the industry , We not only bring shopping experience to consumers , Promote the digital transformation and empowerment of technology to the industry . Today's algorithm model is just a small step , Taobao technology will continue to iterate our life and Technology 、 The relationship with the world .”